In the electronic content publishing industry, it is desirable for a content publisher (e.g., a website provider) to present its users not only with interesting, relevant and engaging content in an initial form (e.g., a webpage), but also provide users of the publisher's content with additional recommended content. In the rapidly changing electronic content landscape, the publisher seeks ways to filter the massive pool of possible content recommendations in order to identify a recommendation that is likely to be of interest to the user. Advantageously, optimized filtering of the possible content increases the user's consumption of the recommended content, achieving a higher level of user engagement and strengthening the user's relationship with the publisher, while increasing the content publisher's revenue.